This project encompasses a wide scope of statistical collaboration with neuroscientists and clinical neurologists, and the development of statistical methods to address problems encountered in collaborative studies. The focus of collaborative research is on statistical planning and design of experiments, statistical analysis and modeling of data, and statistical inference. Examples of current studies include: prevalence studies of neurological diseases in the U.S., Argentina and Italy; case-control study of protein microarray data of autism and control samples; analysis of the relationship of cytokines, neurotrophins and growth factors to cerebral palsy in very pre-term children; clinical trial of the effectiveness of magnesium sulfate for the prevention of white matter lesions in infants from high-risk pregnancies; statistical modeling of changes in PET imaging of patients with epilepsy; design and analysis of Phase I/II clinical trials for the evaluation of stroke treatment; population prevalence studies of epilepsy; longitudinal modeling of gray/white matter development in healthy children; longitudinal MRI study of corpus callosum development in healthy children; statistical models for spectroscopic imaging of the brain; analysis and statistical modeling of mechanisms of use-dependent plasticity in human motor cortex; the relationship of seizure frequency to hippocampus volume in temporal epilepsy; post operative changes in cerebral metabolism in temporal lobe epilepsy; estimation of the time distribution of new lesions and recurrent stroke using MRI; determination of spatial acuity thresholds for dystonia patients and healthy controls; clinical trial of the effect of training in patients with focal hand dystonia; analysis of a clinical trial of enzyme replacement therapy for the evaluation of bone density in Gaucher patients; and an evaluation of essential tremor with MRI spectroscopy. Statistical research usually derives from problems encountered in collaborative studies. Areas of research include: population screening methods for disease; establishment of reference range values for diagnostic tests; time series models for longitudinal imaging data; Bayesian designs for Phase I/II clinical trials with control of both efficacy and adverse events; quantification of selection bias in surveys; nonlinear response models for nondecreasing, time-dependent multiple compartment systems; analysis methods for protein microarray data; and new likelihood tests for logistic mixture models in time series.